Triple
T20797805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karo language |
E511956
|
entity |
| Predicate | undergoingInfluenceFrom |
P126359
|
FINISHED |
| Object | Indonesian language |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Indonesian language | Statement: [Karo language, undergoingInfluenceFrom, Indonesian language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undergoingInfluenceFrom Context triple: [Karo language, undergoingInfluenceFrom, Indonesian language]
-
A.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
B.
influencedByCurrent
Indicates that something’s state, behavior, or outcome is affected or determined by the current conditions, context, or situation.
-
C.
isUnderInfluenceOf
chosen
Indicates that one entity is affected, controlled, or significantly shaped by the power, authority, or effect of another entity.
-
D.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
E.
hasExternalInfluence
Indicates that one entity affects or alters another entity due to factors or forces originating outside the affected entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2ae2c4c819087f620df31dc1aba |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0575b1c81908d010223fcd1213e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:39 p.m.